Search Results for "open document" - Page 2
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Showing 259 open source projects for "open document"
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AI-Media2Doc
AI tool converting video/audio into structured documents instantly
AI-Media2Doc is a web-based application that uses large language models to convert video and audio content into structured, readable documents in a single workflow. It is designed to transform multimedia inputs into formats such as knowledge notes, summaries, mind maps, and social-style articles, making content easier to review and reuse. AI-Media2Doc emphasizes privacy by processing media locally in the browser using WebAssembly-based ffmpeg, ensuring that original video files are not... -
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RAGFlow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data. -
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Eliza
Autonomous agents for everyone
Build and deploy autonomous AI agents with consistent personalities across Discord, Twitter, and Telegram. Full support for voice, text, and media interactions. Built-in RAG memory system, document processing, media analysis, and autonomous trading capabilities. Supports multiple AI models including Llama, GPT-4, and Claude. Create custom actions, add new platform integrations, and extend functionality through a modular plugin system. Full TypeScript support. -
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chatd
Chat with your documents using local AI
chatd is an open-source desktop application that allows users to interact with their documents through a locally running large language model. The software focuses on privacy and security by ensuring that all document processing and inference occur entirely on the user’s computer without sending data to external cloud services. It includes a built-in integration with the Ollama runtime, which provides a cross-platform environment for running large language models locally. ... -
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MegaParse
File Parser optimised for LLM Ingestion with no loss
MegaParse is a file parser optimized for Large Language Model (LLM) ingestion, ensuring no loss of information. It efficiently parses various document formats, such as PDFs, DOCX, and PPTX, converting them into formats ideal for processing by LLMs. This tool is essential for applications that require accurate and comprehensive data extraction from diverse document types. -
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RAG Web UI
RAG Web UI is an intelligent dialogue system based on RAG
RAG Web UI is an open-source intelligent dialogue system built on retrieval-augmented generation technology, designed to enable users to create AI-powered question answering systems grounded in their own knowledge bases. It combines document retrieval with large language models to provide accurate, context-aware responses based on indexed data rather than generic model knowledge. -
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RAPTOR
The official implementation of RAPTOR
RAPTOR is a retrieval architecture designed to improve retrieval-augmented generation systems by organizing documents into hierarchical structures that enable more effective context retrieval. Traditional RAG systems typically retrieve small text chunks independently, which can limit a model’s ability to understand broader document context. RAPTOR addresses this limitation by recursively embedding, clustering, and summarizing documents to create a tree-structured hierarchy of information.... -
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RAG API
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL
rag_api is an open-source REST API for building Retrieval-Augmented Generation (RAG) systems using LLMs like GPT. It lets users index documents, search semantically, and retrieve relevant content for use in generative AI workflows. Designed for rapid prototyping, it is ideal for chatbot development, document assistants, and knowledge-based LLM apps. -
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Semantra
Multi-tool for semantic search
Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. ... -
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ChatOllama
ChatOllama is an open-source AI chatbot
...The platform also includes higher-level capabilities such as AI agents, document-backed knowledge bases, real-time voice chat, and Model Context Protocol integration for external tools. Its RAG functionality allows document upload and knowledge-base-driven interaction, while vector database support adds more scalable retrieval options. Deployment is streamlined with Docker Compose, and the project also includes internationalization and modular feature toggles for controlling what parts of the system are enabled. ... -
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LlamaParse
Parse files for optimal RAG
LlamaParse is a GenAI-native document parser that can parse complex document data for any downstream LLM use case (RAG, agents). Load in 160+ data sources and data formats, from unstructured, and semi-structured, to structured data (API's, PDFs, documents, SQL, etc.) Store and index your data for different use cases. Integrate with 40+ vector stores, document stores, graph stores, and SQL db providers. -
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GLM-OCR
Accurate × Fast × Comprehensive
GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B), enabling deployment in high-concurrency services and edge environments. ... -
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canvas-editor
Canvas-based WYSIWYG rich text editor with advanced layout tools
canvas-editor is a browser-based rich text editor that renders content using HTML5 Canvas and SVG instead of traditional DOM-based approaches. It is designed to provide a WYSIWYG editing experience similar to word processors, enabling precise control over layout, rendering, and document structure. canvas-editor supports a wide range of formatting and document features, including text styling, tables, images, and embedded elements, all managed through a structured data model. Its architecture... -
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NativeMind Extension
Your fully private, open-source, on-device AI assistant
NativeMindExtension is an open-source browser extension that provides a private, on-device AI assistant designed to run without cloud dependencies. The project is built around a privacy-first model in which conversations, document analysis, translations, and writing assistance stay on the user’s device rather than being sent to external servers. It integrates with local model back ends such as Ollama and also supports WebLLM for quick in-browser trials, giving users a choice between stronger local setups and lighter no-install demonstrations. ... -
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Accomplish
Accomplish is the open source Al coworker that lives on your desktop
Accomplish is an open-source AI desktop agent that automates everyday computer tasks directly on a user’s machine. It can handle file management, document creation, and browser-based workflows through natural language instructions. The system runs locally, ensuring that user data remains private and under full control. It supports integration with multiple AI providers or local models, giving users flexibility in how intelligence is powered. -
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abogen
Generate audiobooks from EPUBs, PDFs and text with captions
abogen is a tool designed to generate audiobooks (or speech narrations) from textual sources such as EPUBs, PDFs, or plain text, with synchronized captions. In other words, it automates the pipeline of reading a digital book (or document), converting its text into speech via a TTS engine, and packaging the result into an audiobook format — likely along with timestamped captions or subtitles that align with the spoken audio. This can be very useful for accessibility, content consumption on... -
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DeepCode
DeepCode: Open Agentic Coding
...It also describes document parsing capabilities aimed at extracting algorithmic and mathematical details from technical materials, translating them into implementable specifications and code. -
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Firebase MCP
Model Context Protocol (MCP) server to interact with Firebase service
A Model Context Protocol (MCP) server that enables Large Language Model (LLM) clients to interact seamlessly with Firebase services, facilitating operations across Authentication, Firestore, and Storage. -
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AutoDev for VSCode
AI-powered coding wizard . Put the most loved AutoDev AI assistant
AutoDev, the AI-powered coding wizard with multilingual support, auto code generation, and a helpful bug-slaying assistant. Customizable prompts and a magic Auto Dev/Testing/Document/Agent feature are included. -
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GitHub Copilot SDK
Multi-platform SDK for integrating GitHub Copilot Agent into apps
The GitHub Copilot SDK is a developer toolkit that enables creators to build custom AI-assisted experiences powered by Copilot models within their own applications, editors, and workflows. Instead of being limited to editors like VS Code, this SDK lets teams embed Copilot-style code suggestions, natural language assistance, and predictive completions anywhere they see fit—such as internal IDEs, browser extensions, documentation portals, or bespoke tools tailored to specific languages or... -
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AI PDF Chatbot LangChain
AI PDF chatbot agent built with LangChain & LangGraph
AI PDF Chatbot LangChain is a full-stack template for building conversational agents that can ingest and answer questions about PDF documents. The project demonstrates how to combine LangChain and LangGraph with a vector database to enable retrieval-augmented question answering over user-provided files. It includes both frontend and backend components, making it suitable as a production starting point rather than just a minimal demo. The system parses uploaded PDFs into document chunks,... -
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Generative AI Use Cases (GenU)
Application implementation with business use cases
AWS Generative AI Use Cases is an open-source repository developed by AWS that provides practical examples and reference implementations for building applications powered by generative artificial intelligence. The project collects a wide range of real-world scenarios that demonstrate how organizations can use large language models and generative AI services within cloud-based architectures. -
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HiClaw
An open source collaborative multi-agent OS
HiClaw is an AI-powered legal assistant framework developed within the AgentScope ecosystem to support intelligent legal reasoning, document analysis, and workflow automation for legal research and compliance tasks. The project combines large language models with agent orchestration systems to process legal documents, interpret regulations, summarize contracts, and assist with legal knowledge retrieval. It is designed to provide structured, explainable workflows that help legal professionals... -
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Lemon AI
Full-stack Open-source Self-Evolving General AI Agent
LemonAI is an open-source full-stack framework for building autonomous AI agents capable of performing complex tasks such as research, programming, data analysis, and document processing. The platform is designed to run primarily on local infrastructure, providing a privacy-focused alternative to cloud-dependent agent platforms. It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external cloud models. ... -
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Chandra
OCR model for complex documents with layout-aware structured outputs
Chandra is an advanced OCR model designed to extract and structure information from complex documents such as tables, forms, handwritten notes, and mathematical content. It focuses on preserving full document layout, meaning that extracted text is accompanied by positional metadata like bounding boxes for each element. Chandra supports multiple output formats including Markdown, HTML, and JSON, making it suitable for downstream processing and integration into data pipelines. It is capable of...
